Article-Journal

• DE-GAM: A dual-encoder graph-attention mixture-of-experts framework for post-crash traffic speed forecasting during freeway all-lane-closure incidents
• Vision-language and generative models in traffic video safety analysis: a computational framework and research agenda
• Personalizing In-Vehicle warnings: A causal machine learning approach to optimizing workload and risk perception
• A Comprehensive Review of Vehicle-Pedestrian Interactions: Crash Analysis and Conflict Assessment Approaches
• Interaction patterns and quantitative risks between right-turning vehicles and pedestrians at signalized intersections: Insights from conflict and crash datasets
• From prediction to explanation: A machine learning and causal mediation framework for roadway crash risk with connected vehicle data
• Real-Time Freeway Crash Occurrence and Type Prediction Using Connected Vehicle Data via a Spatiotemporal BiLSTM-Transformer
• Assessing the safety effectiveness of advanced driver assistance systems
• Joint analysis on pedestrian injury severity across vehicle movements at intersections: Addressing temporal instability and spatial correlations
• Grouped random parameters Poisson-Lindley model with spatial effects addressing crashes at intersections: Insights from visual environment features and spatiotemporal instability
• Tunnel crash severity and congestion duration joint evaluation based on cross-stitch networks
• LSTM + Transformer Real-Time Crash Risk Evaluation Using Traffic Flow and Risky Driving Behavior Data
• Design of Minimum Horizontal Curve Radius in Plateau Areas: Psychophysiological Approach
• Safety analysis of pedestrians distracted by mobile phones at street crossings: Field study in Nanjing
• Difference in perception-reaction time of plain and plateau drivers at expressway exit ramps